• YAKHAK HOEJI
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• v.47 no.3
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• pp.176-179
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• 2003

A library of unlimited number of novel lectins with diverse specificities has been previously generated by randomly mutating the carbohydrate-recognition domain of Maackia amurensis hemagglutinin (MAH). To establish the experimental environment capable of selecting high affinity mutant lectins in E. coli, phage display system was adapted. Carbohydrate binding capacity of two phagemid vectors, pComb3 and pComb8 displaying wild-type MAH lectin was assessed. Specific bindings of pComb3 and pComb8 phages expressing w.t. MAH to affinity-purified polyclonal anti-MAH antibody and to glycophorin was demonstrated. Both phages also showed strong hemagglutinating activity to intact but not sialidase-treated human erythrocytes, which is consistent to the specificity of native MAH. Taken together, two different phage display vectors successfully allowed the expression of active MAH as a fusion protein on the surface of bacteriophage, which will lead to preparation of unique plant lectins with high affinity toward a variety of carbohydrate chains.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.340-344
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• 2007

유비쿼터스 지능공간에서 사람의 행동과 위치를 모니터링하는 것은 서비스 제공을 위해 기본적이며 필수적인 단계이다. 본 논문에서는 스마트 펜던트(SmartPendant)의 카메라 영상과 GPS위치 정보를 이용한 새로운 웨어러블 컴퓨터를 제안한다. 우선, 행동 인식를 위해 영상간에 특정 픽셀 값 차와 옵티컬 플로우를 사용하였으며, 인식이 가능한 행동으로는 걷기, 멈춤, 방향전환이다. 또한, GPS를 이용한 사용자의 위치 정보는 위도와 경도에 대한 스트링값을 패킷값으로 변환하여 지능형 상황인지 서버에 전달된다.

• Annual Conference of KIPS
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• 2014.04a
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• pp.823-825
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• 2014

감시 카메라 환경에서 자동으로 그룹 행동을 인식하는 기술이 최근 많은 관심을 받고 있다. 본 논문에서 제안하는 그룹 해동 인식 시스템은 다른 추가 정보 없이 비디오 프레임만을 인풋으로 받아들여, 자동으로 보행자 탐지, 추적, 행동 인식까지 모두 포괄하는 시스템이다. 시공간 모션 패턴을 만들고 연결 요소들로 모델링 한 뒤 Hidden Markov Model (HMM)을 이용해 그룹 행동을 인식한다. 실험 결과, 기본 논문과 비교하였을 때, 비슷한 인식률을 보이면서 수행 시간을 약 25 배 정도로 획기적으로 단축하였다.

• Annual Conference of KIPS
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• 2013.11a
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• pp.1332-1335
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• 2013

본 논문에서는 키넥트 센서 데이터에 은닉 조건부 랜덤 필드 모델을 적용하여 인간의 일상 행위를 인식하는 시스템을 제안한다. 많은 고수준의 일상 행위들은 다수의 부속 행위들이 순차적 혹은 반복적으로 수행되어 나타나는 하나의 계층구조로 볼 수 있다. 따라서 제안하는 시스템에서는 이러한 고수준의 일상 행위들을 순차성과 계층성을 잘 표현할 수 있는 확률 그래프 모델의 하나인 은닉 조건부 랜덤 필드 모델로 모델링함으로써, 행위 인식률을 높이려고 시도하였다. 또한 제안하는 시스템에서는 효과적인 행위 모델의 학습과 적용을 위해, 모션 특징, 구조 특징, 손 위치 특징과 같은 다양한 종류의 특징들을 키넥트 센서 데이터로부터 추출하여 이들을 이용하였다. 그리고 12 가지 일상 행위들에 관한 코넬 대학의 CAD-60 데이터 집합을 이용한 다양한 실험을 통해, 제안하는 시스템의 우수한 인식 성능을 확인할 수 있었다.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.551-560
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• 2023

Recently, there has been significant research into the recognition of human activities using three-dimensional sequential skeleton data captured by the Kinect depth sensor. Many of these studies employ deep learning models. This study introduces a novel feature selection method for this data and analyzes it using machine learning models. Due to the high-dimensional nature of the original Kinect data, effective feature extraction methods are required to address the classification challenge. In this research, we propose using the first four moments as predictors to represent the distribution of joint sequences and evaluate their effectiveness using two datasets: The exergame dataset, consisting of three activities, and the MSR daily activity dataset, composed of ten activities. The results show that the accuracy of our approach outperforms existing methods on average across different classifiers.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.775-782
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• 2024

This systematic review comprehensively analyzes the application of computer vision in construction productivity measurement and emphasizes the importance of worker accountability in construction sites. It identifies a significant gap in the connection level between input (resources) and output data (products or progress) of productivity monitoring, a factor not adequately addressed in prior research. The review highlights three fundamental groups: input, output, and connection groups. Object detection, tracking, pose, and activity recognition, as the input stage, are essential for identifying characteristics and worker movements. The output phase will mostly focus on progress monitoring, and understanding the interaction of workers with other entities will be discussed in the connection groups. This study offers four research future research directions for the worker accountability monitoring process, such as human-object interaction (HOI), generative AI, location-based management systems (LBMS), and robotic technologies. The successful accountability monitoring will secure the accuracy of productivity measurement and elevate the competitiveness of the construction industry.

• Hwankyungkyoyuk
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• v.23 no.3
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• pp.115-125
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• 2010

This study conducted a survey on recognition of teachers, students, and Parent Teacher Association(PTA) for the Education for Sustainable Development from April to October, 2008. It confirmed a couple of facts, which were summarized as follows; First, among eight educational areas including Environmental Education, Energy Education, Gender Education, World Heritage Education, Multi-cultural Coexistence Education, Peace Education, Education for human rights, and Education for international understanding that UNESCO had offered, this study showed that the 'Environmental Education' is a relatively important area comparing with others. Second, 54.4% of the respondents have agree with the need of the education for sustainable development in the middle school and the high school, and 54.1% of them showed their willingness to participate in the program. Third, because 49.2% of the respondents chose 'important' on the question of 'how important the field education and the experience education are', it looked like most of them agreed with the importance of the field education and the experience education. Fourth, because 61.1% of the responded teachers chose 'need' on the question of 'if it needs relationship with other studies', it looked like most of them agreed with the necessity of relationship with other studies. Fifth, 62.5% of the respondents chose 'no' on the question of 'if they conduct the education for sustainable development Even if some wanted the education for sustainable development, most of them would not do it in the regular curriculum, but in the special activity class or teacher's discretional time. Sixth, most respondents indicated the teacher's class burden and the teacher's lack of knowledge as the problem if the education for sustainable development would be conducted. This result implied that in order to vitalize the education for sustainable development, the teacher's class burden should be reduced and the teacher train program is necessary. Finally, urgent requested studies could improve the education for sustainable development in communities and schools, because the result of the survey showed education, natural observation learning, and visiting ecological parks as important elements.

• Journal of Life Science
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• v.17 no.2 s.82
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• pp.179-184
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• 2007

PTK6, an intracellular protein tyrosine kinase, is significantly overexpressed in a majority of breast cancers and has a role in promoting the proliferation of the cancer cells, but not of normal cells. Here, we report high-level production of the catalytic unit of PTK6 fused with Drosophila peptidoglycan recognition protein (PGRT)-LB, in the baculovirus system. We first found that the PGRP-LB was potentially useful as a fusion partner to increase the yield of heterologous protein in the baculovirus system. The purified recombinant protein exhibited a 1.5-fold activity with much higher yield than the bacterially-expressed protein. The protein expressed in the baculovirus system will be useful for the crystallization to determine its crystal structure helping understand the molecular mechanism of PTK6 and design its inhibitors.

• KSBB Journal
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• v.10 no.3
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• pp.343-348
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• 1995

Human lipocorin-I(LCI) is a calcium ion-dependent and phospholipid-binding protein which exhibits an anti-inflammatory activity by inhibiting phospholipase A2 activity. In this study, the LCI gene containing its own terminator region was joined to GAL10 promoter-ppL (prepro-leader sequence of mating factor a). An ATG start codon of LCI gene was placed at downstream with KR endoprotease recognition site(Lys-Arg) of ppL. Recombinant S. cerevisiae harboring the LCI expression/secretion vector, pYGLPT5, was aerobicall grown on a liquid YPDG medium al $30^{\circ}C$ for 72hys. The whole cell and culture supernatant were separated after centrifugation, and the expressed LCI was analyzed by SDS-PAGE and western blotting methods. A majority fraction of the expressed LCI was found to be accumulated in the intracellular fraction, resulting in very low secretion efficiency of about 7.4%. About $500mg/\ell$ of LCI was extracellularly produced by the fed-batch culture employing the controlledfeeding of glucose and galactose. The secreted LCI was purified by ultrafiltration and hydroxylapatite column chromatography, and a purity of more than 99% was obtained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.67-74
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• 2006

Contort-aware computing technology is one of the key technology of ubiquitous computing in the mobile device environment. Context recognition computing enables computer applications that automatically respond to user's everyday activity to be realized. In this paper, We use accelerometer could sense activity states of the object and apply to mobile devices. This method for estimating human motion states utilizes various statistics of accelerometer data, such as mean, standard variation, and skewness, as features for classification, and is expected to be more effective than other existing methods that rely on only a few simple statistics. Classification algorithm uses simple decision tree instead of existing neural network by considering mobile devices with limited resources. A series of experiments for testing the effectiveness of the our context detection system for mobile applications and ubiquitous computing has been performed, and its result is presented.